ARMA-CIGMN - A neural network model for time series (häftad)
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Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
128
Utgivningsdatum
2015-11-18
Förlag
LAP Lambert Academic Publishing
Medarbetare
Engel Paulo Martins
Illustrationer
black & white illustrations
Dimensioner
229 x 152 x 8 mm
Vikt
200 g
Antal komponenter
1
Komponenter
Paperback
ISBN
9783659798849

ARMA-CIGMN - A neural network model for time series

av Flores Joo Henrique Ferreira, Engel Paulo Martins
Häftad,  Engelska, 2015-11-18
522
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This book presents a new model of neural network for time series analysis and forecasting: the ARMA-CIGMN (Autoregressive Moving Average Classical Incremental Gaussian Mixture Network) model and its analysis. This model is based on modifications made to a reformulated IGMN, the Classical IGMN (CIGMN). The CIGMN is similar to the original IGMN, but based on a classical statistical approach. The modifications to the IGMN algorithm were made to better fit it to time series. The ARMA-CIGMN model demonstrates good forecasts and the modeling procedure can also be aided by known statistical tools as the autocorrelation (acf) and partial autocorrelation functions (pacf), already used in classical statistical time series modeling and also with the original IGMN algorithm models. The ARMA-CIGMN model was evaluated using known series and simulated data.
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